Overview

Dataset statistics

Number of variables18
Number of observations710839
Missing cells1633088
Missing cells (%)12.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory437.5 MiB
Average record size in memory645.3 B

Variable types

NUM11
CAT7

Warnings

Start Time has a high cardinality: 2399 distinct values High cardinality
End Time has a high cardinality: 2442 distinct values High cardinality
Start Centroid Location has a high cardinality: 275 distinct values High cardinality
End Centroid Location has a high cardinality: 293 distinct values High cardinality
Start Centroid Latitude is highly correlated with Start Community Area NumberHigh correlation
Start Community Area Number is highly correlated with Start Centroid LatitudeHigh correlation
Start Census Tract has 328202 (46.2%) missing values Missing
End Census Tract has 328364 (46.2%) missing values Missing
Start Community Area Number has 97389 (13.7%) missing values Missing
End Community Area Number has 97916 (13.8%) missing values Missing
Start Community Area Name has 97389 (13.7%) missing values Missing
End Community Area Name has 97916 (13.8%) missing values Missing
Start Centroid Latitude has 97388 (13.7%) missing values Missing
Start Centroid Longitude has 97388 (13.7%) missing values Missing
Start Centroid Location has 97388 (13.7%) missing values Missing
End Centroid Latitude has 97916 (13.8%) missing values Missing
End Centroid Longitude has 97916 (13.8%) missing values Missing
End Centroid Location has 97916 (13.8%) missing values Missing
Trip Distance is highly skewed (γ1 = 130.443317) Skewed
Accuracy is highly skewed (γ1 = 387.4378225) Skewed
Trip ID has unique values Unique
Trip Distance has 51958 (7.3%) zeros Zeros
Accuracy has 128767 (18.1%) zeros Zeros

Reproduction

Analysis started2020-12-12 22:02:17.473125
Analysis finished2020-12-12 22:03:07.379571
Duration49.91 seconds
Software versionpandas-profiling v2.9.0
Download configurationconfig.yaml

Variables

Trip ID
Categorical

UNIQUE

Distinct710839
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size5.4 MiB
be5fe66c-1c3a-48db-8c14-0afc667f3011
 
1
c0bf6519-b061-40ce-86c7-85e247a3ac06
 
1
1ad743de-6a32-43fa-b1a7-0ec2d5e5b198
 
1
e12f7856-e81b-55e7-9d8d-528e9febf17e
 
1
459978b1-21c2-46a4-80c6-361ff33ffbda
 
1
Other values (710834)
710834 
ValueCountFrequency (%) 
be5fe66c-1c3a-48db-8c14-0afc667f30111< 0.1%
 
c0bf6519-b061-40ce-86c7-85e247a3ac061< 0.1%
 
1ad743de-6a32-43fa-b1a7-0ec2d5e5b1981< 0.1%
 
e12f7856-e81b-55e7-9d8d-528e9febf17e1< 0.1%
 
459978b1-21c2-46a4-80c6-361ff33ffbda1< 0.1%
 
124c35db-6992-c652-124c-35db6992c6521< 0.1%
 
81620dde-5b1e-4d80-b405-6617317982611< 0.1%
 
15ffe587-dd17-51cf-aae5-64e9807eab3c1< 0.1%
 
120b362f-0037-02d8-120b-362f003702d81< 0.1%
 
8eb42b08-a38e-45a5-ba89-db56dd0167de1< 0.1%
 
1adcacc1-2a67-52c9-bc45-3a904f77c9fd1< 0.1%
 
1211aa58-8e64-3ba6-1211-aa588e643ba61< 0.1%
 
1bddd05f-7010-4987-ba8f-73a15f008c581< 0.1%
 
55f7d861-3c14-5ea1-a884-5c4ddac3f00f1< 0.1%
 
c360a98d-4c93-46fd-afe6-fb4c9f0118dc1< 0.1%
 
46b8b54a-47f8-47dd-b2c2-bf96793e1a4e1< 0.1%
 
429e4057-6de0-4637-b36d-dd4cf7b449831< 0.1%
 
7f626360-c66e-447e-8024-6a5f6452b98e1< 0.1%
 
48abfbd0-9c57-400d-be48-1100fdc50e351< 0.1%
 
38fda097-d534-4dbf-aee1-be959d21bf3d1< 0.1%
 
b7361101-8b44-5f41-853f-15ce4bcccb8f1< 0.1%
 
11d96b68-5d67-42d4-11d9-6b685d6742d41< 0.1%
 
72fbaf8e-7e17-415f-a7fc-a38c40a9e1cf1< 0.1%
 
11f0fca6-5ec1-0ef0-11f0-fca65ec10ef01< 0.1%
 
80fff13f-cc71-40b8-b537-6d801bbb5cf21< 0.1%
 
Other values (710814)710814> 99.9%
 
2020-12-12T17:03:09.238171image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique710839 ?
Unique (%)100.0%
2020-12-12T17:03:09.312735image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length36
Median length36
Mean length36
Min length36

Overview of Unicode Properties

Unique unicode characters17
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
-284335611.1%
 
417419426.8%
 
116393426.4%
 
b15151335.9%
 
514774225.8%
 
214743445.8%
 
814392485.6%
 
a14318725.6%
 
914075455.5%
 
013497465.3%
 
e13487885.3%
 
c13324585.2%
 
313291305.2%
 
613281325.2%
 
d13187305.2%
 
f13115265.1%
 
713014905.1%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number1448834156.6%
 
Lowercase Letter825850732.3%
 
Dash Punctuation284335611.1%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
4174194212.0%
 
1163934211.3%
 
5147742210.2%
 
2147434410.2%
 
814392489.9%
 
914075459.7%
 
013497469.3%
 
313291309.2%
 
613281329.2%
 
713014909.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
b151513318.3%
 
a143187217.3%
 
e134878816.3%
 
c133245816.1%
 
d131873016.0%
 
f131152615.9%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-2843356100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Common1733169767.7%
 
Latin825850732.3%
 

Most frequent Common characters

ValueCountFrequency (%) 
-284335616.4%
 
4174194210.1%
 
116393429.5%
 
514774228.5%
 
214743448.5%
 
814392488.3%
 
914075458.1%
 
013497467.8%
 
313291307.7%
 
613281327.7%
 
713014907.5%
 

Most frequent Latin characters

ValueCountFrequency (%) 
b151513318.3%
 
a143187217.3%
 
e134878816.3%
 
c133245816.1%
 
d131873016.0%
 
f131152615.9%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII25590204100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
-284335611.1%
 
417419426.8%
 
116393426.4%
 
b15151335.9%
 
514774225.8%
 
214743445.8%
 
814392485.6%
 
a14318725.6%
 
914075455.5%
 
013497465.3%
 
e13487885.3%
 
c13324585.2%
 
313291305.2%
 
613281325.2%
 
d13187305.2%
 
f13115265.1%
 
713014905.1%
 

Start Time
Categorical

HIGH CARDINALITY

Distinct2399
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.4 MiB
06/22/2019 03:00:00 PM
 
1134
06/28/2019 05:00:00 PM
 
1111
06/22/2019 02:00:00 PM
 
1104
06/21/2019 05:00:00 PM
 
1059
07/11/2019 06:00:00 PM
 
1049
Other values (2394)
705382 
ValueCountFrequency (%) 
06/22/2019 03:00:00 PM11340.2%
 
06/28/2019 05:00:00 PM11110.2%
 
06/22/2019 02:00:00 PM11040.2%
 
06/21/2019 05:00:00 PM10590.1%
 
07/11/2019 06:00:00 PM10490.1%
 
06/22/2019 04:00:00 PM10330.1%
 
07/06/2019 05:00:00 PM10210.1%
 
06/24/2019 06:00:00 PM10030.1%
 
06/28/2019 06:00:00 PM9920.1%
 
06/21/2019 06:00:00 PM9860.1%
 
06/22/2019 05:00:00 PM9630.1%
 
07/03/2019 05:00:00 PM9610.1%
 
06/22/2019 01:00:00 PM9580.1%
 
07/11/2019 07:00:00 PM9580.1%
 
06/26/2019 06:00:00 PM9480.1%
 
06/25/2019 06:00:00 PM9430.1%
 
07/07/2019 04:00:00 PM9420.1%
 
07/12/2019 06:00:00 PM9420.1%
 
06/18/2019 06:00:00 PM9350.1%
 
06/29/2019 04:00:00 PM9290.1%
 
06/20/2019 06:00:00 PM9270.1%
 
06/23/2019 01:00:00 PM9220.1%
 
06/16/2019 03:00:00 PM9210.1%
 
06/20/2019 05:00:00 PM9140.1%
 
06/26/2019 05:00:00 PM9130.1%
 
Other values (2374)68627196.5%
 
2020-12-12T17:03:09.394305image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique21 ?
Unique (%)< 0.1%
2020-12-12T17:03:09.467368image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length22
Median length22
Mean length22
Min length22

Overview of Unicode Properties

Unique unicode characters16
Unique unicode categories4 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
0514877732.9%
 
/14216789.1%
 
14216789.1%
 
:14216789.1%
 
112334117.9%
 
211312687.2%
 
910062266.4%
 
M7108394.5%
 
P5980113.8%
 
73729102.4%
 
83355002.1%
 
62837751.8%
 
31611581.0%
 
51486051.0%
 
41301160.8%
 
A1128280.7%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number995174663.6%
 
Other Punctuation284335618.2%
 
Space Separator14216789.1%
 
Uppercase Letter14216789.1%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
0514877751.7%
 
1123341112.4%
 
2113126811.4%
 
9100622610.1%
 
73729103.7%
 
83355003.4%
 
62837752.9%
 
31611581.6%
 
51486051.5%
 
41301161.3%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
/142167850.0%
 
:142167850.0%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
1421678100.0%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
M71083950.0%
 
P59801142.1%
 
A1128287.9%
 

Most occurring scripts

ValueCountFrequency (%) 
Common1421678090.9%
 
Latin14216789.1%
 

Most frequent Common characters

ValueCountFrequency (%) 
0514877736.2%
 
/142167810.0%
 
142167810.0%
 
:142167810.0%
 
112334118.7%
 
211312688.0%
 
910062267.1%
 
73729102.6%
 
83355002.4%
 
62837752.0%
 
31611581.1%
 
51486051.0%
 
41301160.9%
 

Most frequent Latin characters

ValueCountFrequency (%) 
M71083950.0%
 
P59801142.1%
 
A1128287.9%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII15638458100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
0514877732.9%
 
/14216789.1%
 
14216789.1%
 
:14216789.1%
 
112334117.9%
 
211312687.2%
 
910062266.4%
 
M7108394.5%
 
P5980113.8%
 
73729102.4%
 
83355002.1%
 
62837751.8%
 
31611581.0%
 
51486051.0%
 
41301160.8%
 
A1128280.7%
 

End Time
Categorical

HIGH CARDINALITY

Distinct2442
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.4 MiB
06/22/2019 03:00:00 PM
 
1113
06/22/2019 04:00:00 PM
 
1074
06/28/2019 05:00:00 PM
 
1070
06/22/2019 02:00:00 PM
 
1040
06/21/2019 05:00:00 PM
 
1040
Other values (2437)
705502 
ValueCountFrequency (%) 
06/22/2019 03:00:00 PM11130.2%
 
06/22/2019 04:00:00 PM10740.2%
 
06/28/2019 05:00:00 PM10700.2%
 
06/22/2019 02:00:00 PM10400.1%
 
06/21/2019 05:00:00 PM10400.1%
 
06/28/2019 06:00:00 PM10320.1%
 
07/11/2019 06:00:00 PM10250.1%
 
06/21/2019 06:00:00 PM10230.1%
 
07/06/2019 05:00:00 PM9840.1%
 
06/24/2019 06:00:00 PM9810.1%
 
07/11/2019 07:00:00 PM9690.1%
 
06/18/2019 06:00:00 PM9600.1%
 
06/22/2019 05:00:00 PM9520.1%
 
06/20/2019 06:00:00 PM9480.1%
 
06/26/2019 06:00:00 PM9360.1%
 
07/03/2019 05:00:00 PM9310.1%
 
07/06/2019 06:00:00 PM9230.1%
 
07/07/2019 04:00:00 PM9220.1%
 
06/16/2019 03:00:00 PM9130.1%
 
06/21/2019 07:00:00 PM9110.1%
 
07/03/2019 04:00:00 PM9100.1%
 
07/12/2019 06:00:00 PM9090.1%
 
06/27/2019 06:00:00 PM9090.1%
 
06/29/2019 05:00:00 PM9090.1%
 
07/12/2019 07:00:00 PM9070.1%
 
Other values (2417)68654896.6%
 
2020-12-12T17:03:09.548438image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique58 ?
Unique (%)< 0.1%
2020-12-12T17:03:09.622001image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length22
Median length22
Mean length22
Min length22

Overview of Unicode Properties

Unique unicode characters16
Unique unicode categories4 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
0515150932.9%
 
/14216789.1%
 
14216789.1%
 
:14216789.1%
 
112354007.9%
 
211289567.2%
 
910095136.5%
 
M7108394.5%
 
P6027723.9%
 
73731692.4%
 
83357222.1%
 
62837361.8%
 
31597091.0%
 
51458860.9%
 
41281460.8%
 
A1080670.7%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number995174663.6%
 
Other Punctuation284335618.2%
 
Space Separator14216789.1%
 
Uppercase Letter14216789.1%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
0515150951.8%
 
1123540012.4%
 
2112895611.3%
 
9100951310.1%
 
73731693.7%
 
83357223.4%
 
62837362.9%
 
31597091.6%
 
51458861.5%
 
41281461.3%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
/142167850.0%
 
:142167850.0%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
1421678100.0%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
M71083950.0%
 
P60277242.4%
 
A1080677.6%
 

Most occurring scripts

ValueCountFrequency (%) 
Common1421678090.9%
 
Latin14216789.1%
 

Most frequent Common characters

ValueCountFrequency (%) 
0515150936.2%
 
/142167810.0%
 
142167810.0%
 
:142167810.0%
 
112354008.7%
 
211289567.9%
 
910095137.1%
 
73731692.6%
 
83357222.4%
 
62837362.0%
 
31597091.1%
 
51458861.0%
 
41281460.9%
 

Most frequent Latin characters

ValueCountFrequency (%) 
M71083950.0%
 
P60277242.4%
 
A1080677.6%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII15638458100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
0515150932.9%
 
/14216789.1%
 
14216789.1%
 
:14216789.1%
 
112354007.9%
 
211289567.2%
 
910095136.5%
 
M7108394.5%
 
P6027723.9%
 
73731692.4%
 
83357222.1%
 
62837361.8%
 
31597091.0%
 
51458860.9%
 
41281460.8%
 
A1080670.7%
 

Trip Distance
Real number (ℝ≥0)

SKEWED
ZEROS

Distinct15594
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11977.20099
Minimum0
Maximum215653491
Zeros51958
Zeros (%)7.3%
Memory size5.4 MiB
2020-12-12T17:03:09.696065image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1612
median1366
Q32773
95-th percentile6942
Maximum215653491
Range215653491
Interquartile range (IQR)2161

Descriptive statistics

Standard deviation617755.6435
Coefficient of variation (CV)51.57763021
Kurtosis29504.65111
Mean11977.20099
Median Absolute Deviation (MAD)937
Skewness130.443317
Sum8513861572
Variance3.81622035e+11
MonotocityNot monotonic
2020-12-12T17:03:09.774633image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0519587.3%
 
100094441.3%
 
200062940.9%
 
300043200.6%
 
1637330.5%
 
400030500.4%
 
500020840.3%
 
3219030.3%
 
600016220.2%
 
69215240.2%
 
72415220.2%
 
74015110.2%
 
78814880.2%
 
67514880.2%
 
75614830.2%
 
77214770.2%
 
82014730.2%
 
70814720.2%
 
56314670.2%
 
64314640.2%
 
65914600.2%
 
85214490.2%
 
80414260.2%
 
61114240.2%
 
88514230.2%
 
Other values (15569)60288084.8%
 
ValueCountFrequency (%) 
0519587.3%
 
1346< 0.1%
 
23950.1%
 
34730.1%
 
44670.1%
 
54200.1%
 
64320.1%
 
74110.1%
 
84060.1%
 
93840.1%
 
ValueCountFrequency (%) 
2156534911< 0.1%
 
1293933341< 0.1%
 
1078839741< 0.1%
 
970409041< 0.1%
 
863006011< 0.1%
 
862894571< 0.1%
 
647619191< 0.1%
 
647459231< 0.1%
 
647300121< 0.1%
 
647265621< 0.1%
 

Trip Duration
Real number (ℝ)

Distinct9473
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean722.2299297
Minimum-1642
Maximum110628
Zeros1810
Zeros (%)0.3%
Memory size5.4 MiB
2020-12-12T17:03:09.858705image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-1642
5-th percentile7
Q1189
median407
Q3829
95-th percentile2297
Maximum110628
Range112270
Interquartile range (IQR)640

Descriptive statistics

Standard deviation1312.577602
Coefficient of variation (CV)1.817395747
Kurtosis510.0808989
Mean722.2299297
Median Absolute Deviation (MAD)272
Skewness14.6395409
Sum513389201
Variance1722859.962
MonotocityNot monotonic
2020-12-12T17:03:09.935271image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
465850.9%
 
564800.9%
 
657780.8%
 
355150.8%
 
750160.7%
 
243470.6%
 
842300.6%
 
937560.5%
 
1032680.5%
 
1128600.4%
 
1225410.4%
 
124430.3%
 
1322260.3%
 
1419380.3%
 
018100.3%
 
1517400.2%
 
1615550.2%
 
1714920.2%
 
21612490.2%
 
21112270.2%
 
1812030.2%
 
20111990.2%
 
22111810.2%
 
18611800.2%
 
17111790.2%
 
Other values (9448)63884189.9%
 
ValueCountFrequency (%) 
-16421< 0.1%
 
-8091< 0.1%
 
-6901< 0.1%
 
-6651< 0.1%
 
-6111< 0.1%
 
-5551< 0.1%
 
018100.3%
 
124430.3%
 
243470.6%
 
355150.8%
 
ValueCountFrequency (%) 
1106281< 0.1%
 
987511< 0.1%
 
971071< 0.1%
 
900751< 0.1%
 
839191< 0.1%
 
702841< 0.1%
 
682681< 0.1%
 
679931< 0.1%
 
661591< 0.1%
 
660871< 0.1%
 

Accuracy
Real number (ℝ≥0)

SKEWED
ZEROS

Distinct186
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean764.6577861
Minimum0
Maximum60337000
Zeros128767
Zeros (%)18.1%
Memory size5.4 MiB
2020-12-12T17:03:10.013338image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median10
Q3152
95-th percentile152
Maximum60337000
Range60337000
Interquartile range (IQR)151

Descriptive statistics

Standard deviation109348.7182
Coefficient of variation (CV)143.0034719
Kurtosis176709.7195
Mean764.6577861
Median Absolute Deviation (MAD)9
Skewness387.4378225
Sum543548576
Variance1.195714217e+10
MonotocityNot monotonic
2020-12-12T17:03:10.093407image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
1031473344.3%
 
15216350623.0%
 
012876718.1%
 
17133410.0%
 
100092801.3%
 
200062110.9%
 
300042750.6%
 
400030160.4%
 
500020630.3%
 
600016130.2%
 
700012010.2%
 
80008960.1%
 
90006980.1%
 
100005360.1%
 
110004390.1%
 
12000315< 0.1%
 
13000281< 0.1%
 
14000230< 0.1%
 
15000192< 0.1%
 
17000134< 0.1%
 
16000130< 0.1%
 
18000104< 0.1%
 
1900097< 0.1%
 
2000070< 0.1%
 
2100063< 0.1%
 
Other values (161)6550.1%
 
ValueCountFrequency (%) 
012876718.1%
 
17133410.0%
 
1031473344.3%
 
15216350623.0%
 
100092801.3%
 
200062110.9%
 
300042750.6%
 
400030160.4%
 
500020630.3%
 
600016130.2%
 
ValueCountFrequency (%) 
603370001< 0.1%
 
428940001< 0.1%
 
236150001< 0.1%
 
221870001< 0.1%
 
213830001< 0.1%
 
213690001< 0.1%
 
213670001< 0.1%
 
190600001< 0.1%
 
98180001< 0.1%
 
45820001< 0.1%
 

Start Census Tract
Real number (ℝ≥0)

MISSING

Distinct245
Distinct (%)0.1%
Missing328202
Missing (%)46.2%
Infinite0
Infinite (%)0.0%
Mean1.703152808e+10
Minimum1.70311503e+10
Maximum1.70318435e+10
Zeros0
Zeros (%)0.0%
Memory size5.4 MiB
2020-12-12T17:03:10.176979image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum1.70311503e+10
5-th percentile1.70312205e+10
Q11.70312414e+10
median1.70312832e+10
Q31.7031833e+10
95-th percentile1.70318419e+10
Maximum1.70318435e+10
Range693200
Interquartile range (IQR)591600

Descriptive statistics

Standard deviation298440.1362
Coefficient of variation (CV)1.752280446e-05
Kurtosis-1.987032312
Mean1.703152808e+10
Median Absolute Deviation (MAD)92499
Skewness0.04601466778
Sum6.51689281e+15
Variance8.90665149e+10
MonotocityNot monotonic
2020-12-12T17:03:10.258549image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
1.7031833e+109551313.4%
 
1.70312414e+10311264.4%
 
1.70318331e+10286784.0%
 
1.70312435e+10161772.3%
 
1.70318419e+10154982.2%
 
1.70312415e+10113601.6%
 
1.70312416e+1071601.0%
 
1.70318423e+1070711.0%
 
1.70312421e+1070511.0%
 
1.70312405e+1068201.0%
 
1.7031831e+1066780.9%
 
1.70312206e+1064880.9%
 
1.70318333e+1063380.9%
 
1.70312422e+1056930.8%
 
1.70312214e+1050390.7%
 
1.70318323e+1049490.7%
 
1.70312205e+1048130.7%
 
1.70312222e+1043770.6%
 
1.70312213e+1042320.6%
 
1.70312434e+1038630.5%
 
1.70312423e+1037970.5%
 
1.7031242e+1037550.5%
 
1.70312433e+1031260.4%
 
1.70312403e+1030790.4%
 
1.70312801e+1027120.4%
 
Other values (220)8724412.3%
 
(Missing)32820246.2%
 
ValueCountFrequency (%) 
1.70311503e+102< 0.1%
 
1.70311504e+109< 0.1%
 
1.70311505e+102< 0.1%
 
1.70311506e+1047< 0.1%
 
1.70311507e+1088< 0.1%
 
1.70311508e+10137< 0.1%
 
1.7031151e+1040< 0.1%
 
1.7031151e+10313< 0.1%
 
1.70311511e+10138< 0.1%
 
1.70311512e+10117< 0.1%
 
ValueCountFrequency (%) 
1.70318435e+1056< 0.1%
 
1.70318434e+1015< 0.1%
 
1.70318433e+10112< 0.1%
 
1.70318432e+1088< 0.1%
 
1.70318431e+10217< 0.1%
 
1.7031843e+10175< 0.1%
 
1.70318429e+105130.1%
 
1.70318423e+1070711.0%
 
1.70318422e+1017< 0.1%
 
1.70318421e+1093< 0.1%
 

End Census Tract
Real number (ℝ≥0)

MISSING

Distinct253
Distinct (%)0.1%
Missing328364
Missing (%)46.2%
Infinite0
Infinite (%)0.0%
Mean1.703151696e+10
Minimum1.70310514e+10
Maximum1.70318437e+10
Zeros0
Zeros (%)0.0%
Memory size5.4 MiB
2020-12-12T17:03:10.347125image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum1.70310514e+10
5-th percentile1.70312205e+10
Q11.70312414e+10
median1.70312804e+10
Q31.7031833e+10
95-th percentile1.70318419e+10
Maximum1.70318437e+10
Range792300
Interquartile range (IQR)591600

Descriptive statistics

Standard deviation297727.953
Coefficient of variation (CV)1.74810003e-05
Kurtosis-1.972601007
Mean1.703151696e+10
Median Absolute Deviation (MAD)69898
Skewness0.1230200025
Sum6.514129449e+15
Variance8.864193401e+10
MonotocityNot monotonic
2020-12-12T17:03:10.430697image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
1.7031833e+108059011.3%
 
1.70318331e+10291754.1%
 
1.70312414e+10243623.4%
 
1.70312435e+10174852.5%
 
1.70318419e+10153882.2%
 
1.70312415e+10112201.6%
 
1.70318423e+1093881.3%
 
1.70312421e+1071871.0%
 
1.70312422e+1065300.9%
 
1.70318323e+1063760.9%
 
1.70318333e+1063690.9%
 
1.7031831e+1061390.9%
 
1.70312405e+1058980.8%
 
1.70312416e+1051550.7%
 
1.70312214e+1047820.7%
 
1.70312423e+1047220.7%
 
1.70312434e+1046870.7%
 
1.7031242e+1046660.7%
 
1.70312206e+1042590.6%
 
1.70312213e+1042570.6%
 
1.70312205e+1042200.6%
 
1.70312801e+1041260.6%
 
1.70312222e+1037480.5%
 
1.70312433e+1037130.5%
 
1.70312403e+1035400.5%
 
Other values (228)10449314.7%
 
(Missing)32836446.2%
 
ValueCountFrequency (%) 
1.70310514e+103< 0.1%
 
1.70310707e+1024< 0.1%
 
1.70310715e+103< 0.1%
 
1.70311502e+106< 0.1%
 
1.70311503e+107< 0.1%
 
1.70311504e+108< 0.1%
 
1.70311506e+1073< 0.1%
 
1.70311507e+1089< 0.1%
 
1.70311508e+10189< 0.1%
 
1.7031151e+1064< 0.1%
 
ValueCountFrequency (%) 
1.70318437e+1036< 0.1%
 
1.70318435e+1073< 0.1%
 
1.70318434e+1013< 0.1%
 
1.70318433e+10211< 0.1%
 
1.70318432e+10199< 0.1%
 
1.70318431e+10334< 0.1%
 
1.7031843e+10152< 0.1%
 
1.70318429e+107720.1%
 
1.70318423e+1093881.3%
 
1.70318422e+10215< 0.1%
 

Start Community Area Number
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct30
Distinct (%)< 0.1%
Missing97389
Missing (%)13.7%
Infinite0
Infinite (%)0.0%
Mean24.74810498
Minimum3
Maximum76
Zeros0
Zeros (%)0.0%
Memory size5.4 MiB
2020-12-12T17:03:10.511266image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile19
Q122
median24
Q328
95-th percentile28
Maximum76
Range73
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.281728374
Coefficient of variation (CV)0.1326052389
Kurtosis1.363218258
Mean24.74810498
Median Absolute Deviation (MAD)2
Skewness-0.4330516038
Sum15181725
Variance10.76974112
MonotocityNot monotonic
2020-12-12T17:03:10.580826image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%) 
2819387827.3%
 
2418627726.2%
 
229072812.8%
 
19205632.9%
 
25192772.7%
 
21175032.5%
 
23119061.7%
 
31117211.6%
 
20114691.6%
 
29102511.4%
 
3080801.1%
 
1679921.1%
 
2774671.1%
 
1570821.0%
 
2650730.7%
 
1820670.3%
 
1717660.2%
 
8141< 0.1%
 
7123< 0.1%
 
6038< 0.1%
 
530< 0.1%
 
425< 0.1%
 
324< 0.1%
 
613< 0.1%
 
631< 0.1%
 
Other values (5)5< 0.1%
 
(Missing)9738913.7%
 
ValueCountFrequency (%) 
31< 0.1%
 
530< 0.1%
 
7123< 0.1%
 
8141< 0.1%
 
1570821.0%
 
1679921.1%
 
1717660.2%
 
1820670.3%
 
19205632.9%
 
20114691.6%
 
ValueCountFrequency (%) 
761< 0.1%
 
631< 0.1%
 
613< 0.1%
 
6038< 0.1%
 
581< 0.1%
 
425< 0.1%
 
341< 0.1%
 
331< 0.1%
 
324< 0.1%
 
31117211.6%
 

End Community Area Number
Real number (ℝ≥0)

MISSING

Distinct40
Distinct (%)< 0.1%
Missing97916
Missing (%)13.8%
Infinite0
Infinite (%)0.0%
Mean24.59813223
Minimum2
Maximum67
Zeros0
Zeros (%)0.0%
Memory size5.4 MiB
2020-12-12T17:03:10.655891image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile19
Q122
median24
Q328
95-th percentile29
Maximum67
Range65
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.530747418
Coefficient of variation (CV)0.143537216
Kurtosis5.316649625
Mean24.59813223
Median Absolute Deviation (MAD)2
Skewness-0.5075234357
Sum15076761
Variance12.46617733
MonotocityNot monotonic
2020-12-12T17:03:10.729955image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%) 
2418827226.5%
 
2818182325.6%
 
229257913.0%
 
19203682.9%
 
21187222.6%
 
25183052.6%
 
23156862.2%
 
31133471.9%
 
2097741.4%
 
2995511.3%
 
1689981.3%
 
3089411.3%
 
1574791.1%
 
2767420.9%
 
2648590.7%
 
1723520.3%
 
1821370.3%
 
711540.2%
 
810350.1%
 
54480.1%
 
60160< 0.1%
 
3271< 0.1%
 
621< 0.1%
 
5918< 0.1%
 
1416< 0.1%
 
Other values (15)65< 0.1%
 
(Missing)9791613.8%
 
ValueCountFrequency (%) 
21< 0.1%
 
34< 0.1%
 
42< 0.1%
 
54480.1%
 
621< 0.1%
 
711540.2%
 
810350.1%
 
101< 0.1%
 
114< 0.1%
 
1416< 0.1%
 
ValueCountFrequency (%) 
671< 0.1%
 
663< 0.1%
 
611< 0.1%
 
60160< 0.1%
 
5918< 0.1%
 
5813< 0.1%
 
577< 0.1%
 
563< 0.1%
 
423< 0.1%
 
392< 0.1%
 

Start Community Area Name
Categorical

MISSING

Distinct30
Distinct (%)< 0.1%
Missing97389
Missing (%)13.7%
Memory size5.4 MiB
NEAR WEST SIDE
193878 
WEST TOWN
186277 
LOGAN SQUARE
90728 
BELMONT CRAGIN
20563 
AUSTIN
 
19277
Other values (25)
102727 
ValueCountFrequency (%) 
NEAR WEST SIDE19387827.3%
 
WEST TOWN18627726.2%
 
LOGAN SQUARE9072812.8%
 
BELMONT CRAGIN205632.9%
 
AUSTIN192772.7%
 
AVONDALE175032.5%
 
HUMBOLDT PARK119061.7%
 
LOWER WEST SIDE117211.6%
 
HERMOSA114691.6%
 
NORTH LAWNDALE102511.4%
 
SOUTH LAWNDALE80801.1%
 
IRVING PARK79921.1%
 
EAST GARFIELD PARK74671.1%
 
PORTAGE PARK70821.0%
 
WEST GARFIELD PARK50730.7%
 
MONTCLARE20670.3%
 
DUNNING17660.2%
 
NEAR NORTH SIDE141< 0.1%
 
LINCOLN PARK123< 0.1%
 
BRIDGEPORT38< 0.1%
 
NORTH CENTER30< 0.1%
 
WOODLAWN5< 0.1%
 
LOOP4< 0.1%
 
NEW CITY3< 0.1%
 
NEAR SOUTH SIDE1< 0.1%
 
Other values (5)5< 0.1%
 
(Missing)9738913.7%
 
2020-12-12T17:03:10.820033image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique6 ?
Unique (%)< 0.1%
2020-12-12T17:03:10.899100image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length18
Median length12
Mean length10.43389431
Min length3

Overview of Unicode Properties

Unique unicode characters26
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
E99628513.4%
 
77960010.5%
 
S73971310.0%
 
T6701649.0%
 
W6132928.3%
 
N5933278.0%
 
A5672637.6%
 
R4083605.5%
 
O3780025.1%
 
I2760363.7%
 
D2678303.6%
 
L2039452.7%
 
n1947782.6%
 
G1407121.9%
 
U1317611.8%
 
a973891.3%
 
Q907291.2%
 
P467700.6%
 
M460060.6%
 
H418800.6%
 
K396450.5%
 
B325080.4%
 
V254950.3%
 
C227860.3%
 
F125400.2%
 

Most occurring categories

ValueCountFrequency (%) 
Uppercase Letter634505285.5%
 
Space Separator77960010.5%
 
Lowercase Letter2921673.9%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n19477866.7%
 
a9738933.3%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
E99628515.7%
 
S73971311.7%
 
T67016410.6%
 
W6132929.7%
 
N5933279.4%
 
A5672638.9%
 
R4083606.4%
 
O3780026.0%
 
I2760364.4%
 
D2678304.2%
 
L2039453.2%
 
G1407122.2%
 
U1317612.1%
 
Q907291.4%
 
P467700.7%
 
M460060.7%
 
H418800.7%
 
K396450.6%
 
B325080.5%
 
V254950.4%
 
C227860.4%
 
F125400.2%
 
Y3< 0.1%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
779600100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin663721989.5%
 
Common77960010.5%
 

Most frequent Latin characters

ValueCountFrequency (%) 
E99628515.0%
 
S73971311.1%
 
T67016410.1%
 
W6132929.2%
 
N5933278.9%
 
A5672638.5%
 
R4083606.2%
 
O3780025.7%
 
I2760364.2%
 
D2678304.0%
 
L2039453.1%
 
n1947782.9%
 
G1407122.1%
 
U1317612.0%
 
a973891.5%
 
Q907291.4%
 
P467700.7%
 
M460060.7%
 
H418800.6%
 
K396450.6%
 
B325080.5%
 
V254950.4%
 
C227860.3%
 
F125400.2%
 
Y3< 0.1%
 

Most frequent Common characters

ValueCountFrequency (%) 
779600100.0%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII7416819100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
E99628513.4%
 
77960010.5%
 
S73971310.0%
 
T6701649.0%
 
W6132928.3%
 
N5933278.0%
 
A5672637.6%
 
R4083605.5%
 
O3780025.1%
 
I2760363.7%
 
D2678303.6%
 
L2039452.7%
 
n1947782.6%
 
G1407121.9%
 
U1317611.8%
 
a973891.3%
 
Q907291.2%
 
P467700.6%
 
M460060.6%
 
H418800.6%
 
K396450.5%
 
B325080.4%
 
V254950.3%
 
C227860.3%
 
F125400.2%
 

End Community Area Name
Categorical

MISSING

Distinct40
Distinct (%)< 0.1%
Missing97916
Missing (%)13.8%
Memory size5.4 MiB
WEST TOWN
188272 
NEAR WEST SIDE
181823 
LOGAN SQUARE
92579 
BELMONT CRAGIN
20368 
AVONDALE
 
18722
Other values (35)
111159 
ValueCountFrequency (%) 
WEST TOWN18827226.5%
 
NEAR WEST SIDE18182325.6%
 
LOGAN SQUARE9257913.0%
 
BELMONT CRAGIN203682.9%
 
AVONDALE187222.6%
 
AUSTIN183052.6%
 
HUMBOLDT PARK156862.2%
 
LOWER WEST SIDE133471.9%
 
HERMOSA97741.4%
 
NORTH LAWNDALE95511.3%
 
IRVING PARK89981.3%
 
SOUTH LAWNDALE89411.3%
 
PORTAGE PARK74791.1%
 
EAST GARFIELD PARK67420.9%
 
WEST GARFIELD PARK48590.7%
 
DUNNING23520.3%
 
MONTCLARE21370.3%
 
LINCOLN PARK11540.2%
 
NEAR NORTH SIDE10350.1%
 
NORTH CENTER4480.1%
 
BRIDGEPORT160< 0.1%
 
LOOP71< 0.1%
 
LAKE VIEW21< 0.1%
 
MCKINLEY PARK18< 0.1%
 
ALBANY PARK16< 0.1%
 
Other values (15)65< 0.1%
 
(Missing)9791613.8%
 
2020-12-12T17:03:10.980670image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique4 ?
Unique (%)< 0.1%
2020-12-12T17:03:11.058237image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length18
Median length12
Mean length10.39918322
Min length3

Overview of Unicode Properties

Unique unicode characters27
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
E96979113.1%
 
76921110.4%
 
S7208949.8%
 
T6679129.0%
 
W6084538.2%
 
N5920278.0%
 
A5639227.6%
 
R4059905.5%
 
O3898565.3%
 
I2682253.6%
 
D2632443.6%
 
L2138722.9%
 
n1958322.6%
 
G1435681.9%
 
U1378971.9%
 
a979161.3%
 
Q925891.3%
 
P526840.7%
 
M479910.6%
 
H454840.6%
 
K450110.6%
 
B362430.5%
 
V277410.4%
 
C241410.3%
 
F116120.2%
 
Other values (2)39< 0.1%
 

Most occurring categories

ValueCountFrequency (%) 
Uppercase Letter632918685.6%
 
Space Separator76921110.4%
 
Lowercase Letter2937484.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n19583266.7%
 
a9791633.3%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
E96979115.3%
 
S72089411.4%
 
T66791210.6%
 
W6084539.6%
 
N5920279.4%
 
A5639228.9%
 
R4059906.4%
 
O3898566.2%
 
I2682254.2%
 
D2632444.2%
 
L2138723.4%
 
G1435682.3%
 
U1378972.2%
 
Q925891.5%
 
P526840.8%
 
M479910.8%
 
H454840.7%
 
K450110.7%
 
B362430.6%
 
V277410.4%
 
C241410.4%
 
F116120.2%
 
Y35< 0.1%
 
J4< 0.1%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
769211100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin662293489.6%
 
Common76921110.4%
 

Most frequent Latin characters

ValueCountFrequency (%) 
E96979114.6%
 
S72089410.9%
 
T66791210.1%
 
W6084539.2%
 
N5920278.9%
 
A5639228.5%
 
R4059906.1%
 
O3898565.9%
 
I2682254.0%
 
D2632444.0%
 
L2138723.2%
 
n1958323.0%
 
G1435682.2%
 
U1378972.1%
 
a979161.5%
 
Q925891.4%
 
P526840.8%
 
M479910.7%
 
H454840.7%
 
K450110.7%
 
B362430.5%
 
V277410.4%
 
C241410.4%
 
F116120.2%
 
Y35< 0.1%
 

Most frequent Common characters

ValueCountFrequency (%) 
769211100.0%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII7392145100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
E96979113.1%
 
76921110.4%
 
S7208949.8%
 
T6679129.0%
 
W6084538.2%
 
N5920278.0%
 
A5639227.6%
 
R4059905.5%
 
O3898565.3%
 
I2682253.6%
 
D2632443.6%
 
L2138722.9%
 
n1958322.6%
 
G1435681.9%
 
U1378971.9%
 
a979161.3%
 
Q925891.3%
 
P526840.7%
 
M479910.6%
 
H454840.6%
 
K450110.6%
 
B362430.5%
 
V277410.4%
 
C241410.3%
 
F116120.2%
 
Other values (2)39< 0.1%
 

Start Centroid Latitude
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct275
Distinct (%)< 0.1%
Missing97388
Missing (%)13.7%
Infinite0
Infinite (%)0.0%
Mean41.89878483
Minimum41.77887641
Maximum41.97555516
Zeros0
Zeros (%)0.0%
Memory size5.4 MiB
2020-12-12T17:03:11.134803image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum41.77887641
5-th percentile41.86789231
Q141.88528825
median41.89973715
Q341.91590954
95-th percentile41.93763562
Maximum41.97555516
Range0.1966787448
Interquartile range (IQR)0.03062129245

Descriptive statistics

Standard deviation0.02265581917
Coefficient of variation (CV)0.0005407273568
Kurtosis-0.1019063439
Mean41.89878483
Median Absolute Deviation (MAD)0.01444890182
Skewness0.06787593783
Sum25702851.45
Variance0.0005132861424
MonotocityNot monotonic
2020-12-12T17:03:11.217374image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
41.885288259551313.4%
 
41.90120673492546.9%
 
41.92275986396165.6%
 
41.90602339311264.4%
 
41.87400538309204.3%
 
41.87907673286784.0%
 
41.8941013165072.3%
 
41.89265362161772.3%
 
41.92726074159512.2%
 
41.86789231154982.2%
 
41.93866589120011.7%
 
41.90837594113601.6%
 
41.9000698598681.4%
 
41.8601895987041.2%
 
41.8502661780911.1%
 
41.9243477678921.1%
 
41.9067097171601.0%
 
41.9022009270711.0%
 
41.899669970511.0%
 
41.9119700468201.0%
 
41.8390870166930.9%
 
41.9147877466780.9%
 
41.9293311864880.9%
 
41.8716914563380.9%
 
41.9535818262350.9%
 
Other values (250)15576121.9%
 
(Missing)9738813.7%
 
ValueCountFrequency (%) 
41.778876415< 0.1%
 
41.795430631< 0.1%
 
41.809018523< 0.1%
 
41.81736681< 0.1%
 
41.83006543326< 0.1%
 
41.8361506631< 0.1%
 
41.8382145356< 0.1%
 
41.8388061756< 0.1%
 
41.8390870166930.9%
 
41.83954972137< 0.1%
 
ValueCountFrequency (%) 
41.975555161< 0.1%
 
41.965812081< 0.1%
 
41.960518112< 0.1%
 
41.958790984< 0.1%
 
41.957365774< 0.1%
 
41.956797979< 0.1%
 
41.956778462< 0.1%
 
41.956092932< 0.1%
 
41.955859523< 0.1%
 
41.9540281660340.8%
 

Start Centroid Longitude
Real number (ℝ)

MISSING

Distinct275
Distinct (%)< 0.1%
Missing97388
Missing (%)13.7%
Infinite0
Infinite (%)0.0%
Mean-87.68519717
Minimum-87.89349472
Maximum-87.59492536
Zeros0
Zeros (%)0.0%
Memory size5.4 MiB
2020-12-12T17:03:11.304449image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-87.89349472
5-th percentile-87.76311182
Q1-87.69975406
median-87.67531026
Q3-87.65724247
95-th percentile-87.65251725
Maximum-87.59492536
Range0.2985693607
Interquartile range (IQR)0.04251159342

Descriptive statistics

Standard deviation0.03318030117
Coefficient of variation (CV)-0.0003784025382
Kurtosis0.9100195745
Mean-87.68519717
Median Absolute Deviation (MAD)0.01806778913
Skewness-1.226284776
Sum-53790571.89
Variance0.001100932386
MonotocityNot monotonic
2020-12-12T17:03:11.386520image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
-87.657242479551313.4%
 
-87.67635713492546.9%
 
-87.69915595396165.6%
 
-87.67531026311264.4%
 
-87.66351789309204.3%
 
-87.65704539286784.0%
 
-87.76311182165072.3%
 
-87.65251725161772.3%
 
-87.76550184159512.2%
 
-87.64296873154982.2%
 
-87.71121064120011.7%
 
-87.67093749113601.6%
 
-87.7209188198681.4%
 
-87.7172194787041.2%
 
-87.6675682380911.1%
 
-87.7347401678921.1%
 
-87.6653277471601.0%
 
-87.6560663470711.0%
 
-87.6698374770511.0%
 
-87.6836365268201.0%
 
-87.714002166930.9%
 
-87.676999366780.9%
 
-87.7119813764880.9%
 
-87.6541250963380.9%
 
-87.7234524862350.9%
 
Other values (250)15576121.9%
 
(Missing)9738813.7%
 
ValueCountFrequency (%) 
-87.893494721< 0.1%
 
-87.828895943< 0.1%
 
-87.8060198414480.2%
 
-87.7986731119< 0.1%
 
-87.7980323214860.2%
 
-87.797614884610.1%
 
-87.7968278247< 0.1%
 
-87.79679554236< 0.1%
 
-87.79652374101< 0.1%
 
-87.794816643< 0.1%
 
ValueCountFrequency (%) 
-87.594925365< 0.1%
 
-87.620334831< 0.1%
 
-87.625191874< 0.1%
 
-87.63330944124< 0.1%
 
-87.63397371< 0.1%
 
-87.6426236321280.3%
 
-87.6428042427120.4%
 
-87.64296873154982.2%
 
-87.644209247< 0.1%
 
-87.6487882531< 0.1%
 

Start Centroid Location
Categorical

HIGH CARDINALITY
MISSING

Distinct275
Distinct (%)< 0.1%
Missing97388
Missing (%)13.7%
Memory size5.4 MiB
POINT (-87.6572424682146 41.8852882458388)
95513 
POINT (-87.6763571260391 41.9012067343156)
49254 
POINT (-87.6991559457654 41.9227598585219)
39616 
POINT (-87.6753102573397 41.9060233934322)
 
31126
POINT (-87.6635178867003 41.8740053848845)
 
30920
Other values (270)
367022 
ValueCountFrequency (%) 
POINT (-87.6572424682146 41.8852882458388)9551313.4%
 
POINT (-87.6763571260391 41.9012067343156)492546.9%
 
POINT (-87.6991559457654 41.9227598585219)396165.6%
 
POINT (-87.6753102573397 41.9060233934322)311264.4%
 
POINT (-87.6635178867003 41.8740053848845)309204.3%
 
POINT (-87.65704538762 41.8790767308624)286784.0%
 
POINT (-87.7631118242259 41.8941012961134)165072.3%
 
POINT (-87.6525172461958 41.8926536169898)161772.3%
 
POINT (-87.7655018368979 41.9272607415187)159512.2%
 
POINT (-87.6429687254204 41.8678923093198)154982.2%
 
POINT (-87.7112106378686 41.938665887698)120011.7%
 
POINT (-87.670937488585 41.9083759393656)113601.6%
 
POINT (-87.7209188101033 41.9000698450397)98681.4%
 
POINT (-87.7172194738186 41.8601895923466)87041.2%
 
POINT (-87.6675682255936 41.8502661710639)80911.1%
 
POINT (-87.7347401601846 41.9243477570064)78921.1%
 
POINT (-87.6653277387058 41.906709710732)71601.0%
 
POINT (-87.656066340364 41.9022009180961)70711.0%
 
POINT (-87.6698374693742 41.8996698963096)70511.0%
 
POINT (-87.683636524973 41.91197004191531)68201.0%
 
POINT (-87.7140020956845 41.8390870085266)66930.9%
 
POINT (-87.6769992950319 41.9147877430097)66780.9%
 
POINT (-87.71198136617541 41.9293311773652)64880.9%
 
POINT (-87.6541250863618 41.8716914509744)63380.9%
 
POINT (-87.7234524820666 41.95358181896)62350.9%
 
Other values (250)15576121.9%
 
(Missing)9738813.7%
 
2020-12-12T17:03:11.479600image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique6 ?
Unique (%)< 0.1%
2020-12-12T17:03:11.550161image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length45
Median length42
Mean length36.46716064
Min length3

Overview of Unicode Properties

Unique unicode characters22
Unique unicode categories8 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
8271023510.5%
 
721700568.4%
 
620658178.0%
 
419769447.6%
 
119425277.5%
 
216478066.4%
 
516354976.3%
 
915652286.0%
 
313584355.2%
 
12269024.7%
 
.12269024.7%
 
011961594.6%
 
P6134512.4%
 
O6134512.4%
 
I6134512.4%
 
N6134512.4%
 
T6134512.4%
 
(6134512.4%
 
-6134512.4%
 
)6134512.4%
 
n1947760.8%
 
a973880.4%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number1826870470.5%
 
Uppercase Letter306725511.8%
 
Space Separator12269024.7%
 
Other Punctuation12269024.7%
 
Open Punctuation6134512.4%
 
Dash Punctuation6134512.4%
 
Close Punctuation6134512.4%
 
Lowercase Letter2921641.1%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n19477666.7%
 
a9738833.3%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
P61345120.0%
 
O61345120.0%
 
I61345120.0%
 
N61345120.0%
 
T61345120.0%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
1226902100.0%
 

Most frequent Open Punctuation characters

ValueCountFrequency (%) 
(613451100.0%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-613451100.0%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
8271023514.8%
 
7217005611.9%
 
6206581711.3%
 
4197694410.8%
 
1194252710.6%
 
216478069.0%
 
516354979.0%
 
915652288.6%
 
313584357.4%
 
011961596.5%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.1226902100.0%
 

Most frequent Close Punctuation characters

ValueCountFrequency (%) 
)613451100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Common2256286187.0%
 
Latin335941913.0%
 

Most frequent Latin characters

ValueCountFrequency (%) 
P61345118.3%
 
O61345118.3%
 
I61345118.3%
 
N61345118.3%
 
T61345118.3%
 
n1947765.8%
 
a973882.9%
 

Most frequent Common characters

ValueCountFrequency (%) 
8271023512.0%
 
721700569.6%
 
620658179.2%
 
419769448.8%
 
119425278.6%
 
216478067.3%
 
516354977.2%
 
915652286.9%
 
313584356.0%
 
12269025.4%
 
.12269025.4%
 
011961595.3%
 
(6134512.7%
 
-6134512.7%
 
)6134512.7%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII25922280100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
8271023510.5%
 
721700568.4%
 
620658178.0%
 
419769447.6%
 
119425277.5%
 
216478066.4%
 
516354976.3%
 
915652286.0%
 
313584355.2%
 
12269024.7%
 
.12269024.7%
 
011961594.6%
 
P6134512.4%
 
O6134512.4%
 
I6134512.4%
 
N6134512.4%
 
T6134512.4%
 
(6134512.4%
 
-6134512.4%
 
)6134512.4%
 
n1947760.8%
 
a973880.4%
 

End Centroid Latitude
Real number (ℝ≥0)

MISSING

Distinct293
Distinct (%)< 0.1%
Missing97916
Missing (%)13.8%
Infinite0
Infinite (%)0.0%
Mean41.89905047
Minimum41.77184916
Maximum42.00157215
Zeros0
Zeros (%)0.0%
Memory size5.4 MiB
2020-12-12T17:03:11.617719image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum41.77184916
5-th percentile41.86018959
Q141.88528825
median41.89973715
Q341.91920702
95-th percentile41.93866589
Maximum42.00157215
Range0.2297229873
Interquartile range (IQR)0.03391877183

Descriptive statistics

Standard deviation0.0230969406
Coefficient of variation (CV)0.0005512521249
Kurtosis-0.07910840333
Mean41.89905047
Median Absolute Deviation (MAD)0.01498704298
Skewness0.03523701861
Sum25680891.71
Variance0.0005334686653
MonotocityNot monotonic
2020-12-12T17:03:11.697287image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
41.885288258059011.3%
 
41.90120673467546.6%
 
41.92275986381995.4%
 
41.87907673291754.1%
 
41.87400538289184.1%
 
41.90602339243623.4%
 
41.89265362174852.5%
 
41.8941013158002.2%
 
41.92726074157222.2%
 
41.86789231153882.2%
 
41.90006985125231.8%
 
41.93866589122981.7%
 
41.90837594112201.6%
 
41.9022009293881.3%
 
41.8502661790471.3%
 
41.8601895979331.1%
 
41.8390870174821.1%
 
41.899669971871.0%
 
41.9535818270551.0%
 
41.9243477667611.0%
 
41.8995893765300.9%
 
41.9540281663860.9%
 
41.9192070263760.9%
 
41.8716914563690.9%
 
41.9147877461390.9%
 
Other values (268)17783625.0%
 
(Missing)9791613.8%
 
ValueCountFrequency (%) 
41.771849163< 0.1%
 
41.775930291< 0.1%
 
41.778876413< 0.1%
 
41.796185613< 0.1%
 
41.808916372< 0.1%
 
41.809018521< 0.1%
 
41.810879577< 0.1%
 
41.817366813< 0.1%
 
41.8299222518< 0.1%
 
41.83006543309< 0.1%
 
ValueCountFrequency (%) 
42.001572151< 0.1%
 
41.985015191< 0.1%
 
41.978829984< 0.1%
 
41.975171532< 0.1%
 
41.9680684716< 0.1%
 
41.965812084< 0.1%
 
41.960674926< 0.1%
 
41.960518117< 0.1%
 
41.958790985< 0.1%
 
41.957365776< 0.1%
 

End Centroid Longitude
Real number (ℝ)

MISSING

Distinct293
Distinct (%)< 0.1%
Missing97916
Missing (%)13.8%
Infinite0
Infinite (%)0.0%
Mean-87.6855336
Minimum-87.82889594
Maximum-87.59492536
Zeros0
Zeros (%)0.0%
Memory size5.4 MiB
2020-12-12T17:03:11.774881image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-87.82889594
5-th percentile-87.76311182
Q1-87.69996837
median-87.67531026
Q3-87.65724247
95-th percentile-87.65251725
Maximum-87.59492536
Range0.233970582
Interquartile range (IQR)0.04272589707

Descriptive statistics

Standard deviation0.03331799858
Coefficient of variation (CV)-0.0003799714413
Kurtosis0.9422835867
Mean-87.6855336
Median Absolute Deviation (MAD)0.01806778913
Skewness-1.207384391
Sum-53744480.31
Variance0.001110089029
MonotocityNot monotonic
2020-12-12T17:03:11.856925image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
-87.657242478059011.3%
 
-87.67635713467546.6%
 
-87.69915595381995.4%
 
-87.65704539291754.1%
 
-87.66351789289184.1%
 
-87.67531026243623.4%
 
-87.65251725174852.5%
 
-87.76311182158002.2%
 
-87.76550184157222.2%
 
-87.64296873153882.2%
 
-87.72091881125231.8%
 
-87.71121064122981.7%
 
-87.67093749112201.6%
 
-87.6560663493881.3%
 
-87.6675682390471.3%
 
-87.7172194779331.1%
 
-87.714002174821.1%
 
-87.6698374771871.0%
 
-87.7234524870551.0%
 
-87.7347401667611.0%
 
-87.6747187765300.9%
 
-87.7633999163860.9%
 
-87.6714490363760.9%
 
-87.6541250963690.9%
 
-87.676999361390.9%
 
Other values (268)17783625.0%
 
(Missing)9791613.8%
 
ValueCountFrequency (%) 
-87.828895943< 0.1%
 
-87.811605743< 0.1%
 
-87.8060198419840.3%
 
-87.804531061< 0.1%
 
-87.7986731137< 0.1%
 
-87.7980323215490.2%
 
-87.797614884510.1%
 
-87.7968278264< 0.1%
 
-87.79679554166< 0.1%
 
-87.79652374103< 0.1%
 
ValueCountFrequency (%) 
-87.594925363< 0.1%
 
-87.596183582< 0.1%
 
-87.6203348312< 0.1%
 
-87.6251918770< 0.1%
 
-87.626762753< 0.1%
 
-87.633309448090.1%
 
-87.63397378< 0.1%
 
-87.6426236325630.4%
 
-87.6428042441260.6%
 
-87.64296873153882.2%
 

End Centroid Location
Categorical

HIGH CARDINALITY
MISSING

Distinct293
Distinct (%)< 0.1%
Missing97916
Missing (%)13.8%
Memory size5.4 MiB
POINT (-87.6572424682146 41.8852882458388)
80590 
POINT (-87.6763571260391 41.9012067343156)
46754 
POINT (-87.6991559457654 41.9227598585219)
 
38199
POINT (-87.65704538762 41.8790767308624)
 
29175
POINT (-87.6635178867003 41.8740053848845)
 
28918
Other values (288)
389287 
ValueCountFrequency (%) 
POINT (-87.6572424682146 41.8852882458388)8059011.3%
 
POINT (-87.6763571260391 41.9012067343156)467546.6%
 
POINT (-87.6991559457654 41.9227598585219)381995.4%
 
POINT (-87.65704538762 41.8790767308624)291754.1%
 
POINT (-87.6635178867003 41.8740053848845)289184.1%
 
POINT (-87.6753102573397 41.9060233934322)243623.4%
 
POINT (-87.6525172461958 41.8926536169898)174852.5%
 
POINT (-87.7631118242259 41.8941012961134)158002.2%
 
POINT (-87.7655018368979 41.9272607415187)157222.2%
 
POINT (-87.6429687254204 41.8678923093198)153882.2%
 
POINT (-87.7209188101033 41.9000698450397)125231.8%
 
POINT (-87.7112106378686 41.938665887698)122981.7%
 
POINT (-87.670937488585 41.9083759393656)112201.6%
 
POINT (-87.656066340364 41.9022009180961)93881.3%
 
POINT (-87.6675682255936 41.8502661710639)90471.3%
 
POINT (-87.7172194738186 41.8601895923466)79331.1%
 
POINT (-87.7140020956845 41.8390870085266)74821.1%
 
POINT (-87.6698374693742 41.8996698963096)71871.0%
 
POINT (-87.7234524820666 41.95358181896)70551.0%
 
POINT (-87.7347401601846 41.9243477570064)67611.0%
 
POINT (-87.6747187652597 41.8995893675262)65300.9%
 
POINT (-87.7633999111184 41.9540281621501)63860.9%
 
POINT (-87.6714490286271 41.9192070176705)63760.9%
 
POINT (-87.6541250863618 41.8716914509744)63690.9%
 
POINT (-87.6769992950319 41.9147877430097)61390.9%
 
Other values (268)17783625.0%
 
(Missing)9791613.8%
 
2020-12-12T17:03:11.950005image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique4 ?
Unique (%)< 0.1%
2020-12-12T17:03:12.025069image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length45
Median length42
Mean length36.42841347
Min length3

Overview of Unicode Properties

Unique unicode characters22
Unique unicode categories8 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
8265622910.3%
 
721752688.4%
 
620921228.1%
 
419645837.6%
 
119485247.5%
 
516255806.3%
 
916205676.3%
 
216023796.2%
 
313173235.1%
 
012433384.8%
 
12258464.7%
 
.12258464.7%
 
P6129232.4%
 
O6129232.4%
 
I6129232.4%
 
N6129232.4%
 
T6129232.4%
 
(6129232.4%
 
-6129232.4%
 
)6129232.4%
 
n1958320.8%
 
a979160.4%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number1824591370.5%
 
Uppercase Letter306461511.8%
 
Space Separator12258464.7%
 
Other Punctuation12258464.7%
 
Open Punctuation6129232.4%
 
Dash Punctuation6129232.4%
 
Close Punctuation6129232.4%
 
Lowercase Letter2937481.1%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n19583266.7%
 
a9791633.3%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
P61292320.0%
 
O61292320.0%
 
I61292320.0%
 
N61292320.0%
 
T61292320.0%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
1225846100.0%
 

Most frequent Open Punctuation characters

ValueCountFrequency (%) 
(612923100.0%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-612923100.0%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
8265622914.6%
 
7217526811.9%
 
6209212211.5%
 
4196458310.8%
 
1194852410.7%
 
516255808.9%
 
916205678.9%
 
216023798.8%
 
313173237.2%
 
012433386.8%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.1225846100.0%
 

Most frequent Close Punctuation characters

ValueCountFrequency (%) 
)612923100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Common2253637487.0%
 
Latin335836313.0%
 

Most frequent Latin characters

ValueCountFrequency (%) 
P61292318.3%
 
O61292318.3%
 
I61292318.3%
 
N61292318.3%
 
T61292318.3%
 
n1958325.8%
 
a979162.9%
 

Most frequent Common characters

ValueCountFrequency (%) 
8265622911.8%
 
721752689.7%
 
620921229.3%
 
419645838.7%
 
119485248.6%
 
516255807.2%
 
916205677.2%
 
216023797.1%
 
313173235.8%
 
012433385.5%
 
12258465.4%
 
.12258465.4%
 
(6129232.7%
 
-6129232.7%
 
)6129232.7%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII25894737100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
8265622910.3%
 
721752688.4%
 
620921228.1%
 
419645837.6%
 
119485247.5%
 
516255806.3%
 
916205676.3%
 
216023796.2%
 
313173235.1%
 
012433384.8%
 
12258464.7%
 
.12258464.7%
 
P6129232.4%
 
O6129232.4%
 
I6129232.4%
 
N6129232.4%
 
T6129232.4%
 
(6129232.4%
 
-6129232.4%
 
)6129232.4%
 
n1958320.8%
 
a979160.4%
 

Interactions

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2020-12-12T17:03:02.402288image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T17:03:02.584946image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T17:03:02.764600image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Correlations

2020-12-12T17:03:12.087623image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2020-12-12T17:03:12.215233image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2020-12-12T17:03:12.341341image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2020-12-12T17:03:12.471954image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.
2020-12-12T17:03:12.597061image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Missing values

2020-12-12T17:03:03.953623image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T17:03:04.700265image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T17:03:06.261609image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-12T17:03:06.682472image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Sample

First rows

Trip IDStart TimeEnd TimeTrip DistanceTrip DurationAccuracyStart Census TractEnd Census TractStart Community Area NumberEnd Community Area NumberStart Community Area NameEnd Community Area NameStart Centroid LatitudeStart Centroid LongitudeStart Centroid LocationEnd Centroid LatitudeEnd Centroid LongitudeEnd Centroid Location
0758e9d21-609f-5479-8e2c-5e8f6425820207/01/2019 05:00:00 PM07/01/2019 05:00:00 PM42131NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
1ff33490c-254a-5af2-9315-d6b2a45b07f706/29/2019 06:00:00 PM06/29/2019 06:00:00 PM6318311NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
2f8a25729-e853-40f3-9200-7eea9f9c45f209/16/2019 01:00:00 PM09/16/2019 01:00:00 PM7773210NaNNaNNaN25.0NaNAUSTINNaNNaNNaN41.894101-87.763112POINT (-87.7631118242259 41.8941012961134)
311d42b99-e839-346c-11d4-2b99e839346c06/24/2019 07:00:00 PM06/24/2019 07:00:00 PM91735910NaNNaN25.025.0AUSTINAUSTIN41.894101-87.763112POINT (-87.7631118242259 41.8941012961134)41.894101-87.763112POINT (-87.7631118242259 41.8941012961134)
40c226130-0fa6-518f-8fe6-219b9fa5f42f07/12/2019 07:00:00 PM07/12/2019 07:00:00 PM02180NaNNaN21.021.0AVONDALEAVONDALE41.938666-87.711211POINT (-87.7112106378686 41.938665887698)41.938666-87.711211POINT (-87.7112106378686 41.938665887698)
511ed0125-e5b6-6ab6-11ed-0125e5b66ab607/13/2019 03:00:00 PM07/13/2019 03:00:00 PM11242410NaNNaN21.021.0AVONDALEAVONDALE41.938666-87.711211POINT (-87.7112106378686 41.938665887698)41.938666-87.711211POINT (-87.7112106378686 41.938665887698)
61690f90b-0a0a-402d-b493-ed351d7e094607/20/2019 06:00:00 PM07/20/2019 06:00:00 PM1725114110NaNNaN21.021.0AVONDALEAVONDALE41.938666-87.711211POINT (-87.7112106378686 41.938665887698)41.938666-87.711211POINT (-87.7112106378686 41.938665887698)
737dc7e7f-0e46-4bf6-b07d-8396fe3f0ccd08/20/2019 04:00:00 PM08/20/2019 04:00:00 PM0710NaNNaN21.021.0AVONDALEAVONDALE41.938666-87.711211POINT (-87.7112106378686 41.938665887698)41.938666-87.711211POINT (-87.7112106378686 41.938665887698)
86c4daee2-7820-4c10-ba20-136cfa399e8609/26/2019 08:00:00 AM09/26/2019 08:00:00 AM060110NaNNaN21.021.0AVONDALEAVONDALE41.938666-87.711211POINT (-87.7112106378686 41.938665887698)41.938666-87.711211POINT (-87.7112106378686 41.938665887698)
9b1a423cc-4544-4edc-9cdf-857a952d98c206/30/2019 08:00:00 PM06/30/2019 09:00:00 PM1107251910NaNNaN21.021.0AVONDALEAVONDALE41.938666-87.711211POINT (-87.7112106378686 41.938665887698)41.938666-87.711211POINT (-87.7112106378686 41.938665887698)

Last rows

Trip IDStart TimeEnd TimeTrip DistanceTrip DurationAccuracyStart Census TractEnd Census TractStart Community Area NumberEnd Community Area NumberStart Community Area NameEnd Community Area NameStart Centroid LatitudeStart Centroid LongitudeStart Centroid LocationEnd Centroid LatitudeEnd Centroid LongitudeEnd Centroid Location
710829ee350f69-d233-5ce3-a339-da8c8c2f6d9e07/03/2019 07:00:00 PM07/03/2019 07:00:00 PM111036701.703124e+101.703124e+1024.024.0WEST TOWNWEST TOWN41.899507-87.679600POINT (-87.6796003361319 41.8995065454147)41.892478-87.664739POINT (-87.6647387878606 41.8924781700026)
710830f740d28b-27ea-4183-af7c-364266c5a40508/04/2019 08:00:00 AM08/04/2019 08:00:00 AM1555348152NaNNaN24.024.0WEST TOWNWEST TOWN41.901207-87.676357POINT (-87.6763571260391 41.9012067343156)41.901207-87.676357POINT (-87.6763571260391 41.9012067343156)
710831e28e355e-b890-5f15-8c82-a09daaa2222706/20/2019 09:00:00 PM06/20/2019 09:00:00 PM1351143701.703124e+101.703124e+1024.024.0WEST TOWNWEST TOWN41.899507-87.679600POINT (-87.6796003361319 41.8995065454147)41.899422-87.684490POINT (-87.6844900067498 41.8994219493757)
710832f4350bf6-f033-416b-9a12-093676bc041308/15/2019 06:00:00 PM08/15/2019 07:00:00 PM5661131521.703124e+101.703124e+1024.024.0WEST TOWNWEST TOWN41.906707-87.684686POINT (-87.6846857728006 41.9067070904476)41.906023-87.675310POINT (-87.6753102573397 41.9060233934322)
710833f8dd5c1c-fb6c-5d07-8f11-8ab71560feca09/17/2019 07:00:00 PM09/17/2019 07:00:00 PM406501.703124e+101.703124e+1024.024.0WEST TOWNWEST TOWN41.899670-87.669837POINT (-87.6698374693742 41.8996698963096)41.899670-87.669837POINT (-87.6698374693742 41.8996698963096)
710834db29a731-9ab0-5428-8368-bea758cac4fe07/24/2019 04:00:00 PM07/24/2019 04:00:00 PM2251470NaNNaN24.024.0WEST TOWNWEST TOWN41.901207-87.676357POINT (-87.6763571260391 41.9012067343156)41.901207-87.676357POINT (-87.6763571260391 41.9012067343156)
710835f644d8ce-a32d-5c1c-ad92-ca01ef86b9f908/30/2019 04:00:00 PM08/30/2019 04:00:00 PM59530101.703124e+101.703124e+1024.024.0WEST TOWNWEST TOWN41.899670-87.669837POINT (-87.6698374693742 41.8996698963096)41.908376-87.670937POINT (-87.670937488585 41.9083759393656)
710836fe97d758-f9eb-4314-85c0-058d56019e3907/06/2019 03:00:00 PM07/06/2019 03:00:00 PM12393211521.703124e+101.703124e+1024.024.0WEST TOWNWEST TOWN41.892433-87.669624POINT (-87.6696237770638 41.8924327728614)41.899670-87.669837POINT (-87.6698374693742 41.8996698963096)
710837e6687f9e-531f-cff9-1a1f-ae71c7f759b606/29/2019 11:00:00 PM06/29/2019 11:00:00 PM160655510NaNNaN24.024.0WEST TOWNWEST TOWN41.901207-87.676357POINT (-87.6763571260391 41.9012067343156)41.901207-87.676357POINT (-87.6763571260391 41.9012067343156)
710838f554df2f-4e4f-5b15-ab56-30199016dcda09/05/2019 08:00:00 PM09/05/2019 09:00:00 PM16562011.703124e+101.703124e+1024.024.0WEST TOWNWEST TOWN41.906023-87.675310POINT (-87.6753102573397 41.9060233934322)41.906710-87.665328POINT (-87.6653277387058 41.906709710732)